In practice, parametric copulas \(C(\text{$u$};\text{$\theta $})\)  with parameter vector \(\text{$\theta $}\)  are almost always used
in statistical modelling, with [1]}, [2]} and [3]}
giving overviews of choices.
However, the implicit copulas of elliptical distributions, and more recently skew elliptical distributions,
are common choices for capturing dependence in many applications. An
attractive feature is that because elliptical and skew elliptical
distributions are closed under marginalization, so are their implicit copulas.
